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Continental Shelf Research

journal homepage: www.elsevier.com/locate/csr

Double fronts in the Yellow Sea in summertime identified using sea surfacetemperature data of multi-scale ultra-high resolution analysis

Lei Lina,⁎, Dongyan Liua, Chongxin Luob, Lian Xiec

a State Key Laboratory of Estuarine and Coastal Research, East China Normal University, No. 500 Dongchuan Road, Shanghai 200241, Chinab Key Laboratory of Marine Environment and Ecology, Ministry of Education, Ocean University of China, Qingdao, Chinac Department of Marine, Earth and Atmospheric Sciences, North Carolina State University, Raleigh, NC, USA

A R T I C L E I N F O

Keywords:Yellow SeaThermal frontRemote sensingSSTTidal mixingTopography

A B S T R A C T

Fronts are ubiquitous phenomena in oceans, and they play a significant role in marine hydrodynamics andecology. During the stratified season of a shelf sea, the coastal front is usually considered as a single front, i.e.,the tidal mixing front. However, using high resolution (~1 km) Multi-scale Ultra-high Resolution (MUR) analysissea surface temperature (SST) data, this study observes persistent double fronts along the Yellow Sea coast insummertime. The double fronts comprise the well-known offshore tidal mixing front and a nearshore front, andthe nearshore front has not been previously reported. The climatological (2002–2017) monthly mean resultshows that the double fronts with two SST gradient peaks exceeding ~2 °C/100 km and opposite SST gradientdirections basically remain unchanged from June to August, whereas the frontal spacing decreases in September.Analyses based on a two-layer concept model suggest that a topographic slope along with tidal mixing couldinduce the pattern of double fronts. The frontogenesis of nearshore thermal front could be associated with thedifferent responses of the water column of different water depths to insolation. The offshore movement of thenearshore front in September could be related to the fast cooling of nearshore water and intensified offshorewind, and the topographic slope is important for determining the pattern of double fronts (loose or tight). Thisstudy shows a new pattern of coastal fronts in the stratified season, and indicates the significance of high re-solution satellite data. The discovery of the double front pattern implies the influence of coastal fronts during thestratified season on marine ecology and environment in a shelf sea might be underestimated.

1. Introduction

Oceanic fronts defined as narrow zones of intensified horizontalgradients of water properties are common and important marine phe-nomena (Joyce, 1983; Belkin et al., 2009; Acha et al., 2015). Frontscould act as dynamic barriers to momentum and offshore water trans-port (Belkin et al., 2009; Chen et al., 2002). Fronts could increaseprimary production by fertilizing the surface euphotic zone (Chen et al.,2003), could induce phytoplankton bloom, and may develop into redtides (Pingree et al., 1975). A front as a convergence zone could alsoaffect the distribution of zooplankton, larva, fish, and even sea birds(Durazo et al., 1998; Lee et al., 2005; Lough and Manning, 2001;Schultes et al., 2013; Woodson and Litvin, 2015). To explore thestructure and variation of fronts is significant for marine hydro-dynamics and ecology.

The Yellow Sea, which has a mean depth of ~44m, an area of~380,000 km2 and is located at the north of the East China Sea and

surrounded by China and the Korean Peninsula, is part of the westernPacific marginal sea (Fig. 1). The Yellow Sea, which has high pro-ductivity, has important fishing grounds for surrounding countries (Jinet al., 2003). Coastal fronts play an important role in Yellow Seaecology and fisheries (e.g., Huang et al., 2010; Wei et al., 2003; Liuet al., 2003).

With the advances in satellites and numerical models, patterns ofYellow Sea fronts that were difficult to observe from in situ data havebeen investigated and gradually recognized. In wintertime, prevailingsouthern cool currents forced by the northerly East Asian monsoonwind occur along the coasts of both China and the Korean Peninsula,while a compensated warm current (i.e., the Yellow Sea Warm Current)flows north basically along the western flank of the central trough inthe Yellow Sea (Su, 2001; Huang et al., 2005). Strong sea surfacecooling and the topography function together with the shear betweenthe cool coastal current and Yellow Sea warm current induced strongSST coastal fronts (SST gradient was ~3–8 °C/100 km) along the

https://doi.org/10.1016/j.csr.2019.02.004Received 19 June 2018; Received in revised form 24 December 2018; Accepted 10 February 2019

⁎ Corresponding author.E-mail address: llin@sklec.ecnu.edu.cn (L. Lin).

Continental Shelf Research 175 (2019) 76–86

Available online 11 February 20190278-4343/ © 2019 Elsevier Ltd. All rights reserved.

T

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Shandong, Jiangsu, and Korean coasts (Hickox et al., 2000; Huanget al., 2010; Wang et al., 2012). From spring to summer, the Yellow SeaCool Water Mass at the bottom of the central Yellow Sea graduallyforms, and the intensified sea surface heating induces the strong stra-tification in summertime (Zhang et al., 2008). Due to the high tidaldissipation, a tidal mixing front that separates the onshore well mixedwater and offshore stratified water occurs along the Yellow Sea coast.Zhao (1985, 1987) investigated the location of the tidal front in theYellow Sea by using the Simpson–Hunter index k (Simpson Amp andHunter, 1974), and their results suggested that the tidal front occurredbasically at k=1.8–2.0 and roughly along the 40m isobath. Lie (1989)confirmed the tidal front in the southeastern Yellow Sea via an in situCTD survey. Hickox et al. (2000) used 12 years of Pathfinder SST datawith ~9 km resolution to detect the climatology and seasonal varia-bility of Yellow Sea fronts and found that fronts were weak in summercompared to winter, which was due to the surface solar heatingwarming the sea surface and smoothing out the SST filed in summer(Hickox et al., 2000; Huang et al., 2010). The results from an oceannumerical model suggested that the weak surface thermal front insummer corresponded to a strong subsurface thermal front (Park andChu, 2006). Based on simulations of a numerical model with horizontal1/12° resolution (~9 km), Liu et al. (2003) and Lü et al. (2010) in-vestigated the current structure and the coastal cold water belts inducedby Yellow Sea tidal mixing fronts. By using eight-years cloud-pene-trating microwave imager data (6–22 km resolution) from the TropicalRain Measuring Mission (TRMM) satellite, Huang et al. (2010) identi-fied seasonal SST fronts in the Yellow Sea and indicated that the frontsin the stratified months were expressed as tidal fronts (monthly meanSST gradient was ~2–4 °C/100 km). However, there was a blind zone of~25 km at the coast in TRMM results due to the inherent defect ofmicrowave measurements.

Previous studies using satellite or model data of relatively coarseresolution (≥9 km) have provided a general pattern of the tidal mixingfront in the Yellow Sea during summertime. However, the finer frontal

structure in the Yellow Sea, especially near the coast, is not clear due tothe limitation of data spatial resolution. In this study, using high re-solution (~1 km) Multi-scale Ultra-high Resolution SST analysis data(Chin et al., 2017), we explored the finer features of fronts in the YellowSea. Interestingly, we found a distinct but not previously reportednearshore front in summertime that occurred along with the well-known tidal mixing front, forming a double front pattern in the YellowSea summertime. The discovery of the double fronts could imply adouble or intensified impact of fronts on coastal hydrodynamics andecology during the stratified season.

This paper is organized as follows. Section 2 introduces the datasource and the frontal-detection method. The characteristics of thedouble fronts are presented in Section 3. The mechanism of the doublefronts formation and variation are discussed in Section 4. Finally, abrief conclusion is given in Section 5.

2. Data and method

2.1. SST data source

In this study, Multi-scale Ultra-high Resolution (MUR) analysis SSTproducts from the Jet Propulsion Laboratory (JPL) were used to detectoceanic fronts. The MUR analysis SST data merged from multiple sa-tellites and in situ data are a global field produced daily on a0.01°× 0.01° grid with a resolution of ~1 km from 2002 to 2017 (Chinet al., 2013, 2017). According to Chin et al. (2017), the global rootmean squares difference between MUR and the Multi-product Ensembleanalysis data is about 0.36 °C, which is comparable to other SST pro-ducts, e.g., Optimum Interpolation SST analysis from NOAA NationalCenter for Environmental Information, Operational Sea Surface Tem-perature and Sea Ice Analysis from the UK Met Office, and CMC SSTanalysis from the Canadian Meteorological Center. MUR SST data havebeen successfully used to diagnose oceanic fronts (e.g., Vazquez-Cuervoet al., 2013, 2017) and used in research on coastal jets, coastal up-welling and the warm SST anomaly (e.g., Gentemann et al., 2017;Patricola and Chang, 2016; Wiafe and Nyadjro, 2015). More informa-tion about MUR SST data can be found at http://podaac.jpl.nasa.gov/Multi-scale_Ultra-high_Resolution_MUR-SST. In this study, the climato-logical (2002–2017) monthly mean SST data created from the dailydata by NOAA ERDDAP (http://coastwatch.pfeg.noaa.gov/erddap)were used for the frontal detection.

In addition, to confirm the presence of the double fronts, the cli-matological monthly mean SST of the Moderate Resolution ImagingSpectroradiometer (MODIS, 2003–2017) and Advanced Very HighResolution Radiometer (AVHRR, 1982–2012) data were used. TheMODIS and AVHRR SST data were also download from NOAA ERDDAP.For the analysis on the formation and variation of the double fronts,climatological monthly mean QuickScat sea surface wind data(2000–2009) provided by NOAA ERDDAP and net heat flux data(1981–2010) provided by NOAA NCEP-NCAR Reanalysis 1 data(https://www.esrl.noaa.gov/psd/data/gridded/data.ncep.reanalysis.derived.html) were used.

2.2. Frontal detection

The SST front is usually characterized by a band with higher SSTgradient magnitude than background. The gradient algorithm devel-oped by Belkin and O'Reilly (2009) is used to diagnose the positions andintensities of SST fronts. Based on the contextual feature-preservingfilter and traditional gradient method, the algorithm can efficientlyremove data noise and have a good shape-preservation (Belkin andO'Reilly, 2009). This algorithm has been widely used in studies ofoceanic fronts (e.g., Karimova, 2014; Liu and Hou, 2012; Zeng et al.,2014). The front detection algorithm is presented as below briefly.

1) Pre-processing the data using contextual median filter (MF) until

Fig. 1. The topography of the Yellow Sea. The grey lines are the water depthisobaths. The red dashed lines denote the four transects for the double frontsshown in Fig. 4 (For interpretation of the references to color in this figure le-gend, the reader is referred to the web version of this article).

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http://podaac.jpl.nasa.gov/Multi-scale_Ultra-high_Resolution_MUR-SSThttp://podaac.jpl.nasa.gov/Multi-scale_Ultra-high_Resolution_MUR-SSThttp://coastwatch.pfeg.noaa.gov/erddaphttps://www.esrl.noaa.gov/psd/data/gridded/data.ncep.reanalysis.derived.htmlhttps://www.esrl.noaa.gov/psd/data/gridded/data.ncep.reanalysis.derived.html

iterative MF convergence. In the process of filtering, the data keepunchanged if the window center is a significant 5-point extremum in5× 5 windows, otherwise if the window center is a spike (ex-tremum in 3× 3 windows) the data will be filtered by a 2D 3×3median filter.

2) Calculating the gradient magnitude for fronts. The gradient iscomputed by using the Sobel operator consisting of 3×3 kernels:

= ⎡

⎣⎢

− +− +− +

⎤

⎦⎥ =

⎡

⎣⎢

+ + +

− − −

⎤

⎦⎥G A G A

1 0 12 0 21 0 1

* ,1 2 1

0 0 01 2 1

*x y(1)

where A is the data from step 1), Gx, Gy are two images which containapproximations for derivate in horizontal and vertical directions, and *is the convolution sign. Then, the SST gradient magnitude (GM) can becalculated as:

= +GM G Δx G Δy( / ) ( / )x y2 2 (2)

The above processes and calculations were all carried out by usingMatlab in this study. Finally, the SST gradient in units of °C/100 km canbe derived. The more detailed description of the algorithm can be foundin Belkin and O'Reilly (2009).

To compare the cross-shore variation of SST in different months,SST deviation was derived using the SST minus the transect mean ofSST. And the SST data pre-processed by using contextual median filterwas used to calculate the SST deviation.

3. Results

3.1. Location and monthly variation of the double front

The climatological monthly mean SST gradients indicate that frontsin the Yellow Sea are obvious throughout the year and relatively strongin wintertime (results not shown). The fronts occur along the ShandongPeninsula, Jiangsu coast and Korean Peninsula. The general pattern andseasonal variation of the fronts are basically consistent with previousstudies (Zhao, 1987; Hickox et al., 2000; Huang et al., 2010; Lie, 1989;Lü et al., 2010; Wang et al., 2012). However, the results from June toSeptember show that distinct and basically parallel double fronts occuralong the Yellow Sea east coast (Fig. 2). The double fronts consist ofnearshore fronts and offshore fronts, which are respectively indicatedby blue and black arrows in Fig. 2. The nearshore fronts and the off-shore fronts are roughly along the 10m and 40m isobaths, respectively.The location of the offshore fronts agrees with the well-known tidalmixing front in the Yellow Sea from previous studies (e.g., Zhao, 1987;Huang et al., 2010; Lü et al., 2010). The SST gradient magnitudes ofboth the nearshore and offshore fronts are in basically the same orderand are greater than 2 °C/100 km. The double fronts in Seohan Bay (SB)and Kyunggi Bay (KB) are clearer due to their large frontal spacing,whereas the double fronts along the southern Liaodong Peninsula (SLP)and the southwestern Korean Peninsula (SKP) have two relatively closefronts. The location of the double fronts from June to August basicallyremains unchanged, while in September, the nearshore fronts in SB andKB move offshore, and the spacing of the two double fronts apparentlydecreases. The SST gradient directions of the nearshore and offshorefronts are basically opposite, i.e., landwards and seawards, respectively(Fig. 3). A double front is also present at the Jiangsu coast, though it isnot very obvious due to the weak offshore SST front (basically< 2 °C/100 km).

3.2. Loose and tight double fronts

To further analyze the characteristics of double fronts, four transectsacross the clear double fronts at SB, KB, SLP and SKP are selected(Transects I–IV in Fig. 1). The transects are selected basically along theSST gradient direction and perpendicular to isobaths. The variations inSST gradient magnitude, SST deviation, together with water depth

along the transects are shown in Fig. 4. The detailed data on themaximum SST gradients of the double fronts and corresponding waterdepths and locations are presented in Table 1.

In the transect SST gradients shown in Fig. 4a-d, two apparentgradient peaks greater than 2 °C/100 km indicate a double front patternalong each transect. In general, the double front patterns along Trans-ects I and II are similar, and both have large frontal spacings, whereasthe frontal spacings along Transects III and IV are relatively small.Depending on the frontal spacing, we classify the double fronts as twotypes, namely, loose double fronts (Transects I and II) and tight doublefronts (Transects III and IV).

For the two loose double fronts from June to August, two SST gra-dient peaks occur offshore at 30–40 km and 120–130 km, respectively(Fig. 4a and b). The average spacing of the two gradient peaks is~90 km. The water depths at the SST gradient peaks of the nearshoreand offshore fronts are approximately 10m and 40m, respectively(Table 1). In addition, the SST gradient magnitudes of the fronts areslightly larger in August than in the other three months. In September,the nearshore front has an obvious offshore movement of ~30 km. Thewater depth at the maximum SST gradient of the nearshore frontsdeepens to ~20m. However, the offshore tidal mixing fronts basicallyremain unchanged. The spacing of two double fronts declines by~30 km. The maximum SST gradient of both double fronts in Sep-tember decrease by ~20% compared to August.

For the two tight double fronts, two SST gradient peaks with smallerspacing (~40 km) than that of the loose double fronts occur offshore at10–20 km and 50–60 km, respectively (Fig. 4c and d). For Transect III,the location of the double fronts basically remains unchanged fromJune to September, whereas the SST gradient of double fronts is rela-tively strong in August. In September, the SST gradient of the nearshorefront decreases, while the double front spacing experiences no obviouschange. For Transect IV, the pattern of the double fronts basically re-mains unchanged from June to August. In September, the double frontsmove offshore obviously, especially for the offshore front. This may bedue to Transect IV being close to the East China sea and the influence ofthe shelf circulation from the south.

To clearly show the frontal SST gradient formation, the SST devia-tion along the transects was calculated from the SST minus the transectmean of the SST. As shown in Fig. 4e-h, the SST deviations are basicallythe same from June to August. Offshore SST cold anomalies exist be-tween the nearshore and the offshore fronts. In addition, the landwardand seaward increases in SST correspond to the nearshore and offshorefronts, respectively, which could induce the opposite directions of SSTgradient of the double fronts. In September, the SST cold anomalies ofTransects I, II, and IV move offshore, which is consistent with the off-shore movement of fronts.

Both transects with loose double fronts show a gentle topographicslope with a slope ratio of ~0.35‰ (Fig. 4e and f), while the topo-graphy is much steeper for the tight double front transects (Fig. 4g andh). This indicates that the topographic slope may play an important rolein the double frontal spacing.

4. Discussion

4.1. Providing confidence in the presence of the double fronts

The double fronts in the Yellow Sea are observed in the monthlymean MUR satellite analysis data. The double or multiple fronts patternhas been found in the Zhe-Min coastal front zone (induced by themeeting between the China eastern coastal cold current and Taiwanwarm current) in winter (He et al., 2015) and the Patagonian shelfbreak front zone (Franco et al., 2008). However, to our knowledge, thedouble front pattern occurring along the tidal mixing front during thestratified season in a shelf sea has not been reported.

Although the MUR data accuracy in the Yellow Sea has not beenevaluated by in situ data, several aspects could provide confidence in

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the presence of the double fronts. First, some studies have suggestedfronts can be effectively detected based on gradient algorithms whenapplied on monthly mean satellite SSTs (e.g., Ullman and Cornillon,1999; Franco et al., 2008). Second, offshore cold SST anomalies withinthe double fronts induced the landwards and seawards SST gradients ofthe double fronts. The locations and timings of cold SST belts from MUR(Fig. 5) are consistent with the in situ observations in the Ocean atlas(Chen et al., 1992) and model results (Lü et al., 2010). Third, the doublefronts are also detected by other satellite data sets, including for ex-ample, those of the MODIS and AVHRR (see Fig. 6). The MODIS andAVHRR results basically agree with the occurrences, locations andtimings of the double fronts in the Yellow Sea, although the intensityhave slight differences and the tight double fronts are not very clear dueto the relatively coarse spatial resolution (~4 km) of MODIS andAVHRR data.

The data with relatively coarse resolution (≥9 km) used by previousstudies on Yellow Sea fronts missed the nearshore front in summertime,thus could not detect the double fronts. The impact of the data re-solution on the frontal detection is investigated by averaging the ~1 kmresolution MUR data into the coarse resolutions of 9 km and 25 km. Asshown in Fig. 7, the coarse resolution data can detect the offshore tidalmixing front but not the nearshore front. Therefore, the fine spatialresolution (at least 4 km) data is necessary for detecting the doublefront.

4.2. The formation and monthly variation of the double fronts

The offshore SST cold anomaly, which induced the SST gradient ofboth sides and the opposite gradient direction, was the key factor in theformation of the double fronts. Lü et al. (2010) noticed the SST anomalybeside the tidal mixing front in the Yellow Sea and suggested it wasinduced by the upwelling from the tidal mixing front. However, thethermal balance analysis from an ocean model by Ren et al. (2014)showed that the vertical diffusion and net radiation flux were dominantterms and were roughly balanced near the tidal mixing front in theYellow Sea. This suggests that the tidal mixing could predominatelyinduce the offshore SST cold anomaly, while the upwelling could besecondary. Therefore, in this section, we offer an explanation of theformation of the offshore cold SST anomaly based on a two-layer con-cept model with only slope topography and vertical mixing, and thendiscuss the formation and variation of the double fronts. According tothe model results of Lü et al. (2010), tide plays a dominant role invertical mixing in the nearshore water. Thus, it is assumed that thevertical mixing is induced only by tide motion in the concept model.And the concept model did not contain the horizontal diffusion whichmight be induced by some hydrodynamic processes, for instance, tidalhorizontal dispersion, horizontal current shears, frontal instabilities,and intra-tidal and fortnight tidal variations.

In summertime, the strong stratification occurs in the Yellow Sea

Fig. 2. Climatological monthly means of SST gradient magnitude (°C/100 km) in the Yellow Sea from June to September. The blue and black arrows indicate thenearshore and offshore fronts of double fronts, respectively. The nearshore and offshore black lines are the 10m and 40m isobaths, respectively (For interpretation ofthe references to color in this figure legend, the reader is referred to the web version of this article).

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due to the strong surface heating (Fig. 8). Assuming uniform surfaceheating and no tidal mixing, the summer Yellow Sea could be idealizedas two layers, i.e., the warm upper mixed layer and the cold bottomlayer (Fig. 9a). The temperatures of the upper and bottom layers are T1and T2, respectively. In the Yellow Sea east, the water depth variesbasically linearly along the double front transect (see Fig. 4e-h).Therefore, an idealized linear topography is used in the concept model.In addition, SST in nearshore waters (offshore distance< 20 km) wasbasically uniform according to the observation (Fig. 4e-f), which mightbe induced by the strong tidal dispersion in the shallow waters.Therefore, the temperature in nearshore waters shallower than themixed layer depth (i.e., x < X0) is assumed to be uniform and un-changed during the tidal mixing.

The offshore tidal mixing front separating the well-mixed waterwith stratified water is basically along the 40m isobaths in the YellowSea (Fig. 2). Therefore, the water shallower than 40m becomes verti-cally well-mixed after adding the tidal mixing as shown in Fig. 9b-d. Invertically well-mixed water, the thermal inertia of a water column isproportional to the bottom depth, which determines the temperaturechange rate of the water column (e.g., Xie et al., 2002). Deep waterwarms more slowly than nearshore shallow water. Due to the differentresponses of the water column to insolation at different depths, ap-parent offshore SST cold anomalies occur between the nearshore andoffshore warm waters after tidal mixing, which is consistent with thetransect SST pattern in Fig. 4e-h. Then, two strong SST gradients nearX0 and X1 correspond to the nearshore front and the offshore tidalmixing front, respectively, whose location be basically consistent withthe satellite result.

The temperature structure near X1 is a typical and well-known tidalmixing front (e.g., Heijst, 1985; Acha et al., 2015; Krause et al., 1986).

Therefore, we only focus on the nearshore front. As shown in Fig. 9aand b, the temperature of the well-mixed water becomes verticallyuniform and equals the vertical temperature average, as below.

=+ ⋅ −+ ⋅ −

∈T x T D T SR xD SR x

x( ) ( X )( X )

, [X , X ]MLML

1 2 0

00 1

(3)

where x is the offshore distance, DML denotes the upper mixed layerdepth, SR denotes the slope ratio, X0 is the offshore distance of theintersection of the interface and the sea floor, X1 is the offshore distanceof the 40m water depth, and T1 and T2 are the temperatures in theupper layer and lower layer, respectively. Then, the horizontal gradientof the temperature (gT) can be derived by the partial derivative of T(x)with respect to x as below.

=∂

∂=

−+ ⋅ −

∈gT x T xx

D SR T TD SR x

x( ) ( ) ( )[ ( X )]

, (X , X )MLML

2 1

02 0 1 (4)

According to Expression (4), |gT| increases landwards and deceasesseawards. The total heat content of the bottom water is basically linearincrease with increasing distance from the coast. Due to mixing with awater body of increasing depth, the effect of the cold bottom water onthe heat content of the entire water column is decreasing seawards.Therefore, the temperature gradient is greater nearshore than offshore.When →x X0 (i.e., the location where the strong nearshore front oc-curs), the magnitude of SST gradient reached a maximum and is ex-pressed as below.

=−

+gTSR T T

D(X ) ( )

ML0

2 1

(5)

This expression suggests that the intensity of the nearshore front isrelated to mixed layer depth, the slope ratio, and the temperature

Fig. 3. Climatological monthly mean of SST gradient vectors in the Yellow sea from June to September. Only vectors with gradient magnitudes greater than 1 °C/100 km are shown.

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difference between the upper and lower layers. According to the ob-servation by Zhao (1989), −T T2 1 is approximately 10 °C in summer-time. The SR is ~0.35‰ according to the topography of the loosedouble fronts (Fig. 4e and f). For the case from June to August, DML is~10m (Fig. 8). Then, gT (X )0 is ~35 °C/100 km for the nearshore front,

according to Expression (5). This indicates that the SST gradient in-duced by the slope topography and tidal vertical mixing is enough forthe formation of the nearshore front of double fronts (3–4 °C/100 km).Therefore, results of the concept model suggest that a slope topographyalong with tidal mixing could induce the SST double front pattern. In

Fig. 4. The climatological monthly (June to September) mean SST gradient magnitudes, temperature deviations, and water depths along Transects I–IV in Fig. 1(a-d)show the SST gradients for the four months along Transects I–IV, respectively. The blue and black arrows roughly indicate the nearshore and the offshore fronts. (e-h)show the SST deviations for the four months along Transects I- IV, respectively. Black dotted lines denote the variations in water depth along transects (Forinterpretation of the references to color in this figure legend, the reader is referred to the web version of this article).

Table 1The maximum SST gradients of the double fronts and corresponding water depths and locations for the four transects.

Transect Month Maximum SST gradient (°C/100 km) Water depth (m) Location (offshore distance, km) Frontal spacing (km)

Front a Front b Front a Front b Front a Front b

I Jun. 3.6 2.3 5 46 31 128 97Jul. 3.8 2.8 6 45 37 125 88Aug. 4.3 3.3 10 44 42 121 79Sep. 3.5 2.8 23 44 70 124 54

II Jun. 2.8 2.6 11 48 40 144 104Jul. 2.1 2.3 11 43 41 126 85Aug. 2.8 2.7 11 46 41 114 73Sep. 2.1 2.4 22 43 78 122 44

III Jun. 1.7 1.8 11 44 9 60 51Jul. 2.4 2.8 11 31 10 51 41Aug. 3.8 4.8 12 32 7 48 41Sep. 2.0 5.2 11 36 9 54 45

IV Jun. 2.8 2.2 7 55 26 70 44Jul. 3.3 2.1 7 20 24 49 25Aug. 3.7 2.4 6 20 20 48 28Sep. 3.4 2.3 17 60 34 85 51

Note. Fronts a and b denote the nearshore and the offshore fronts of the double fronts, respectively.

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reality, the monthly mean SST gradient of the nearshore front fromMUR data is much less than that of the concept model, which may besmoothed by strong surface heating and the ignored horizontal diffu-sion. In addition, −T T2 1 has a maximum in August (Fig. 8), which couldexplain the relatively strong double fronts in August.

For the case in September, due to DML deepening and −T T2 1 de-creasing (Fig. 8), the SST gradient of double fronts will diminish basedon Expression (5). The offshore movement of the nearshore front inSeptember may be related to the drastically reduced surface heat fluxand the intensified offshore wind. The monthly mean of net surface heatflux in September is almost zero and much less than that in June-August(Fig. 10a). There must be heat loss for the Yellow Sea in the second halfof September. The temperature at nearshore waters should go downfaster due to less water depth (i.e., less heat capacity) and higher SST atnearshore waters. The faster reduction in temperature of nearshorewaters could make nearshore temperature approaching that of the ad-jacent offshore water. In addition, the wind from June to August isweak and is southeasterly or easterly basically. In September, the windspeed increases, and the wind turns to be northeasterly (Fig. 10b),which could induce an intensified offshore transport along the YellowSea east coast. The offshore transport could also be helpful for the ex-change of the nearshore waters. As shown in Fig. 11, both of the fastcooling of the nearshore water and the intensified offshore wind couldfacilitate the offshore movement of X0, i.e., the offshore movement ofthe nearshore front in September.

For the tight double fronts case, the topographic slope is obviouslysteeper than that of the loose double fronts case (Fig. 4g-h). Therefore,SR is set to 0.7‰ in the concept model (Fig. 9d). As indicated by pre-vious studies (e.g., Zhao, 1987), the energy of tidal mixing can basicallymaintain the well-mixing of water depth< 40m. That is consistentwith the observation in this study that the offshore fronts basically

occurred along the 40m isobath (Fig. 2). Therefore, X1 (i.e., the off-shore front) was fixed at the point of water depth =40m in the conceptmodel. The offshore front for the transect with a steep slope is closer toshore than that with a gentle slope, and thus is closer to the nearshorefront (Fig. 9d). Therefore, the different topographic slope could be ac-count for the different spacings between the tight and loose doublefronts. According to Expression (5), the SST gradient should have beenstronger than that of the loose tight double fronts case. However, thereis no significantly frontal intensification in satellite results for tightdouble fronts (Fig. 4a-d). This could be due to the strong tidal disper-sion in the nearshore region limiting the SST gradient, which was ig-nored in the concept model.

4.3. Implications from the double fronts

During the stratified season, the coastal front in a shelf sea is usuallyconsidered as a single front, i.e., the tidal mixing front which is theboundary between stratified and well-mixed waters (e.g., Holt andUmlauf, 2008; Lwiza et al., 1991; Pingree and Griffiths, 1978; Schulteset al., 2013). Analyses suggest that the strong tidal mixing together witha slope topography could induce the double front pattern during thestratified season in the Yellow Sea. Therefore, the double front may alsooccur at other seas with the condition of the occurrence of a tidal frontand a suitable slope topography. Whereas, the observation of thedouble fronts needs using high spatial resolution data as the front isusually close to the coastline. With the development of satellite mea-surement, more double front cases and much finer structure of oceanicfront would be detected.

Fronts play a significant role in marine ecology. They could con-verge and enhance the marine biomass (Acha et al., 2015; Woodson andLitvin, 2015; Choi et al., 2017), and could also act as barriers to block

Fig. 5. The climatological monthly (June to September) mean SSTs (°C) from MUR data.

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Fig. 6. The climatological monthly mean SST gradients from June to September as in Fig. 2 but from MODIS (a-d) and AVHRR (e-h) satellite data with ~4 kmresolution. The 2003–2017 and 1982–2012 SST data were used for the MODIS and AVHRR results, respectively.

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Fig. 7. The climatological SST gradients in August and September resulting from the spatial averaging of MUR SST data. (a-b) 9 km. (c-d) 25 km.

Fig. 8. The observed water temperature profiles in the Yellow sea summertime, redrawn after Zhao (1989). (a) shows the locations of observed sites. (b-e) are theobserved results for sites B-E, respectively.

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the material and organism at the coast (Woodson et al., 2012). Thedouble fronts mean an augment of the frontal convergence zone nearcoast, which may enhance the probability of coastal phytoplanktonbloom and the risk of harmful algal blooms (e.g., Pingree et al., 1975).The double fronts may also induce double fencing for the offshoretransport of coastal high nutrient or pollutant in summertime, whichcould intensify nearshore eutrophication and environmental pollutionand influence the connectivity and the recruitment of coastal species(e.g., Woodson et al., 2012). Therefore, the discovery of the doublefronts implies the impact of fronts on marine ecology in the Yellow Seaduring the stratification season might be greatly underestimated be-cause it did not consider the existence of the nearshore front.

5. Conclusions

Double fronts are found in the Yellow Sea in summertime from theclimatological monthly mean MUR satellite SST data with high re-solution (~1 km). The double fronts comprise an offshore tidal mixingfront and a nearshore front with the opposite SST gradient direction.The double fronts are of loose frontal spacing (~90 km) in SB and KB,whereas they are of tight frontal spacing (~40 km) in SLP and SKP. Thedouble fronts basically remain stable in summertime, while their

intensities and spacings decrease in SB and KB in September. Thedouble fronts are also found from the MODIS and AVHRR SST satellitedata. A two-layer concept model including tidal mixing and slope to-pography could basically explain the formation and the general patternof double fronts. The concept model suggests that the increase in uppermixed layer depth in September could reduce the intensity. The off-shore movement of the nearshore front in September may be related tothe fast cooling of nearshore water and intensified offshore wind, andthe slope is a key factor for the pattern of double fronts (loose or tight).This study indicates the necessity of using high resolution satellite datato reveal the fine structure of oceanic fronts.

The double fronts in the Yellow Sea are observed from satellite datain this study. However, field observations and modeling studies areneeded to further confirm the underlying dynamic processes of thedouble fronts and investigate their hydrodynamic characteristics. Theecological and environmental effects of the double fronts are also an-ticipated from future studies.

Fig. 9. Two-layer concept model for double fronts. (a) shows the initial watertemperature distribution of idealized two-layer modes, in which the tempera-tures in the upper layer and lower layer are T1 and T2, respectively. The in-tersection of the interface and the sea floor is at x= X0, and the 40m waterdepth is at x=X1. (b-d) show the temperature distributions after tidal verticalmixing derived from Eq. (3) for different cases. Only the water shallower than40m is vertically mixed. The blue and black arrows indicate the nearshore andthe offshore fronts of double fronts, respectively. (b) and (c) are the cases withthe same slope ratio (SR) of 0.35‰ for idealizing Transects I or II and withupper mixed layer depths (DML) of 10m and 20m, respectively. (d) is the casewith a steeper slope (SR=0.70‰) for idealizing Transects III or IV. The intervalof contours in (b-d) is (T1-T2)/10 (For interpretation of the references to color inthis figure legend, the reader is referred to the web version of this article).

Fig. 10. Climatological monthly mean net heat fluxes (a) and mean sea surfacewinds (b) of the Yellow Sea from QuickScat satellite data (2000–2009) andNOAA NCEP-NCAR reanalysis 1 data (1981–2010), respectively.

Fig. 11. The schematic diagram for the offshore movement of the nearshorefront in September. The darker color denote the higher water temperature alongthe transect. The upper panel shows the initial pattern of temperature, and thelower panel shows the temperature pattern after heat loss and intensification ofoffshore wind.

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Acknowledgments

This work was supported by the National Key FundamentalResearch and Development Plan of China (Grant No. 2016YFC1402106-06) and the National Natural Science Foundation of China (No.41706011). Lei Lin was also supported by the China PostdoctoralScience Foundation funded project and Key Laboratory of CoastalEnvironmental Processes and Ecological Remediation, YICCAS (GrantNo.: 2016KFJJ02). The MUR data were provided by JPL under supportby the NASA MEaSUREs program. The authors thank NOAA ERDDAPfor the MODIS and AVHRR SST data support (http://coastwatch.pfeg.noaa.gov/erddap). The authors declare that the research was conductedin the absence of any commercial or financial relationships that couldbe construed as a potential conflict of interest. The data used can bedownloaded from the given websites.

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Double fronts in the Yellow Sea in summertime identified using sea surface temperature data of multi-scale ultra-high resolution analysisIntroductionData and methodSST data sourceFrontal detection

ResultsLocation and monthly variation of the double frontLoose and tight double fronts

DiscussionProviding confidence in the presence of the double frontsThe formation and monthly variation of the double frontsImplications from the double fronts

ConclusionsAcknowledgmentsReferences